mosaic_evidence_map

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the safety profile is clear. The description adds value by detailing the output structure (relation types, source types, confidence stats, snippets), which is beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences with no fluff: purpose, content, usage. Every sentence is necessary and front-loaded with the most important information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple parameter and existing output schema, the description adequately covers the tool's output (relation types, source types, stats, snippets). No missing critical details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% from the tool description, but the input schema itself already describes the gene_symbol parameter well (e.g., 'Gene symbol of the target'). The tool description adds no additional parameter info, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get the full evidence landscape for a drug target from semantic extraction' and lists the specific relation types and breakdown. This differentiates it from sibling tools like mosaic_get_target_papers or mosaic_target_validation, which focus on specific aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description says 'Use this to understand the strength and breadth of evidence for a target,' providing a clear use case. It does not explicitly mention when not to use or alternatives, but the context with siblings implies it's for a broad overview.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.